Morphological Disambiguation
5 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Morphological Disambiguation
NEMO-Corpus
Latest papers with no code
Camelira: An Arabic Multi-Dialect Morphological Disambiguator
We present Camelira, a web-based Arabic multi-dialect morphological disambiguation tool that covers four major variants of Arabic: Modern Standard Arabic, Egyptian, Gulf, and Levantine.
Breaking Character: Are Subwords Good Enough for MRLs After All?
Large pretrained language models (PLMs) typically tokenize the input string into contiguous subwords before any pretraining or inference.
Breaking Character: Are Subwords Good Enough for MRLs After All?
Large pretrained language models (PLMs) typically tokenize the input string into contiguous subwords before any pretraining or inference.
Morphological Disambiguation from Stemming Data
Kinyarwanda, a morphologically rich language, currently lacks tools for automated morphological analysis.
A Pointer Network Architecture for Joint Morphological Segmentation and Tagging
Neural MD may be addressed as a simple pipeline, where segmentation is followed by sequence tagging, or as an end-to-end model, predicting morphemes from raw tokens.
A Novel Challenge Set for Hebrew Morphological Disambiguation and Diacritics Restoration
One of the primary tasks of morphological parsers is the disambiguation of homographs.
Morphological Disambiguation of South S\'ami with FSTs and Neural Networks
We present a method for conducting morphological disambiguation for South S{\'a}mi, which is an endangered language.
Voted-Perceptron Approach for Kazakh Morphological Disambiguation
This paper presents an approach of voted perceptron for morphological disambiguation for the case of Kazakh language.
Morphological Analysis and Disambiguation for Gulf Arabic: The Interplay between Resources and Methods
In this paper we present the first full morphological analysis and disambiguation system for Gulf Arabic.
Morphological Disambiguation of South Sámi with FSTs and Neural Networks
We present a method for conducting morphological disambiguation for South S\'ami, which is an endangered language.
